Citrus peel waste represents a high-volume, underutilized resource with significant potential for sustainable biopolymer production. This study investigates the extraction and optimization of pectin from three citrus species:
- Citrus sinensis (Sweet Orange)
- Citrus limetta (Sweet Lime)
- Citrus limon (Lemon)
Using citric-acid hydrolysis and Box–Behnken Response Surface Methodology (RSM), the work models, optimizes, and characterizes pectin yield and quality.
This study is supported by structured experimental datasets and tabulated results used for modelling, comparison, and optimization of pectin extraction from citrus peels.
- pectin-extraction-experimental-data.csv
- pectin-extraction-experimental-data.xlsx
The study includes five key analytical tables:
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Table 1: Pectin yield (%) from Citrus sinensis (sweet orange) peels at varied pH and extraction temperature (citric-acid hydrolysis, 2 h)
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Table 2: Pectin yield (%) from Citrus limetta (sweet lime) peels at varied pH and extraction temperature (citric-acid hydrolysis, 2 h)
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Table 3: Pectin yield (%) from Citrus limon (lemon) peels at varied pH and extraction temperature (citric-acid hydrolysis, 2 h)
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Table 4: Box–Behnken RSM optimization outcomes — species-specific operating points and predicted yields (MATLAB R2007b)
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Table 5: Physicochemical characterization of extracted pectin across all Citrus species, benchmarked against commercial citrus pectin (Kaya et al., 2014)
The study employs Response Surface Methodology (RSM) combined with Box–Behnken design to optimize pectin extraction conditions.
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Experimental Design
- Structured combinations of pH and temperature are generated using Box–Behnken design
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Data Collection
- Yield responses are recorded for each experimental condition across three Citrus species
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Model Development
- A quadratic regression model is fitted using MATLAB R2007b
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Response Surface Generation
- The model visualizes how extraction variables influence yield
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Optimization
- Mathematical optimization identifies best operating conditions for maximum yield
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Validation
- Predicted values are compared with experimental outputs to assess model accuracy
RSM enables efficient multi-variable optimization with reduced experimental load while maintaining strong predictive reliability.
- Citrus peel is a valuable biorefinery feedstock, not waste
- Extraction optimized across:
- pH (1.5–4.2)
- Temperature (50–80°C)
- Highest experimental yields:
- C. sinensis → 29.59%
- C. limetta → 32.94%
- C. limon → 36.93%
- RSM modeling achieved strong predictive performance:
- R² up to 0.9618
- Optimized conditions significantly improved process efficiency
- All pectins classified as low-methoxyl
- C. limon shows strongest potential for:
→ Pharmaceutical applications
→ Calcium-induced gel systems
- Experimental extraction of pectin from three citrus species
- RSM-based process optimization using Box–Behnken design
- MATLAB-based quadratic modeling of yield response
- Physicochemical characterization:
- Equivalent weight
- Methoxyl content
- Degree of esterification
- Identification of optimal industrial candidate (C. limon)
| Species | Yield (%) | R² | Optimal pH | Temp (°C) |
|---|---|---|---|---|
| C. sinensis | 29.59 | 0.8927 | 2.81 | 67.49 |
| C. limetta | 32.94 | 0.8311 | 2.77 | 65.16 |
| C. limon | 36.93 | 0.9618 | 3.22 | 60.63 |
📍 Published on Zenodo
🔗 (https://doi.org/10.5281/zenodo.19781987)
📌 DOI: 10.5281/zenodo.19781987
/paper → Published journal paper (PDF) /figures → Process diagrams and response surface plots
- Citric-acid hydrolytic extraction
- One-factor-at-a-time (OFAT) screening
- Box–Behnken experimental design
- Quadratic model fitting (MATLAB R2007b)
Pectin, Citrus Waste, RSM, Box-Behnken, Bioprocess Optimization, Sustainable Materials
Otuekong Edet Bassey
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